Sign Language Letter Recognition Algorithm Based On 7Hu Invariant Moments

Sign Language Recognition is a communication way between the deaf and the health. As a key part of the hand gesture recognition, it has been paid more attention than before with the development of Human Computer Interaction. There are two ways of it: one is vision-based recognition, another is digital glove-based recognition. The former could imitate the human vision and more natural than the latter, so a vision-based method is used here to do the recognition research.Sign language recognition is composed of four parts: collecting images, preprocessing images, extracting image features and recognition. During the preprocessing, image gray transforming, image smoothing, Pyramid segmentation, single threshold segmentation and edge detection are performed on standard sign language images.In the part of feature extraction and recognition, this paper presents a method based on geometric moment features: A sign language recognition algorithm based on 7Hu invariant moments. The edge image of sign language letter is treated by counter-color, and carried on Euclidean Distance Transform (EDT). Its 7Hu moments and the combination moments are calculated. Then binary image also implements EDT, calculates the minimum distance between the image and the template. Finally, the recognition of 30 letter gestures is performed by computing distance, in which different coefficients are set to these two features. The best recognition rate of 90% is achieved.